SGCP
This package is deprecated. It will probably be removed from Bioconductor. Please refer to the package end-of-life guidelines for more information.
This package is for version 3.23 of Bioconductor. This package has been removed from Bioconductor. For the last stable, up-to-date release version, see SGCP.
SGCP: A semi-supervised pipeline for gene clustering using self-training approach in gene co-expression networks
Bioconductor version: Release (3.23)
SGC is a semi-supervised pipeline for gene clustering in gene co-expression networks. SGC consists of multiple novel steps that enable the computation of highly enriched modules in an unsupervised manner. But unlike all existing frameworks, it further incorporates a novel step that leverages Gene Ontology information in a semi-supervised clustering method that further improves the quality of the computed modules.
Author: Niloofar AghaieAbiane [aut, cre]
, Ioannis Koutis [aut]
Maintainer: Niloofar AghaieAbiane <niloofar.abiane at gmail.com>
citation("SGCP")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SGCP")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
| Reference Manual |
Details
| biocViews | Classification, Clustering, DimensionReduction, GeneExpression, GeneSetEnrichment, GraphAndNetwork, Network, NetworkEnrichment, NeuralNetwork, RNASeq, Software, SystemsBiology, Visualization, mRNAMicroarray |
| Version | 1.11.1 |
| In Bioconductor since | BioC 3.17 (R-4.3) (3.5 years) |
| License | GPL-3 |
| Depends | R (>= 4.2.0) |
| Imports | ggplot2, expm, caret, plyr, dplyr, GO.db, annotate, SummarizedExperiment, genefilter, GOstats, RColorBrewer, xtable, Rgraphviz, reshape2, openxlsx, ggridges, DescTools, org.Hs.eg.db, methods, grDevices, stats, RSpectra, graph |
| System Requirements | |
| URL | https://github.com/na396/SGCP |
See More
| Suggests | knitr, rmarkdown, BiocManager, devtools, BiocStyle |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | |
| Windows Binary (x86_64) | SGCP_1.11.1.zip |
| macOS Binary (big-sur-x86_64) | SGCP_1.11.0.tgz |
| macOS Binary (sonoma-arm64) | SGCP_1.11.1.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/SGCP |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/SGCP |
| Package Short Url | https://bioconductor.org/packages/SGCP/ |
| Package Downloads Report | Download Stats |